Crystals -- from sugar and table salt to snowflakes and diamonds -- don't always grow in a straightforward way. Researchers have now captured this journey from amorphous blob to orderly structures. In ...

SPaDe-CSP first predicts most probable space groups and crystal densities using machine learning and then employs an efficient neural network potential for structure refinement. Prediction of crystal ...

UB chemist Jason Benedict and his team spent years developing photoswitchable crystals. Every crystal’s shape is a mirror of the internal arrangement of their molecules, but the molecules in ...

Researchers have devised a mathematical approach to predict the structures of crystals -- a critical step in developing many medicines and electronic devices -- in a matter of hours using only a ...

Crystals—from sugar and table salt to snowflakes and diamonds—don't always grow in a straightforward way. New York University researchers have captured this journey from amorphous blob to orderly ...

BUFFALO, N.Y. — University at Buffalo chemist Jason Benedict and his team spent years developing photoswitchable crystals. Every crystal’s shape is a mirror of the internal arrangement of their ...